'''simple docstring'''






import logging

from transformers.configuration_utils import PretrainedConfig


_UpperCAmelCase    :     Dict         =       logging.getLogger(__name__)







class lowercase_       (		_UpperCamelCase			):







   """simple docstring"""

   __lowerCAmelCase         =   "masked_bert"
   def __init__(      self      :			Dict, UpperCamelCase__      :			Optional[int]=3_05_22, UpperCamelCase__      :			Dict=7_68, UpperCamelCase__      :			Tuple=12, UpperCamelCase__      :			str=12, UpperCamelCase__      :			List[str]=30_72, UpperCamelCase__      :			Tuple="gelu", UpperCamelCase__      :			Dict=0.1, UpperCamelCase__      :			List[Any]=0.1, UpperCamelCase__      :			Optional[Any]=5_12, UpperCamelCase__      :			Optional[Any]=2, UpperCamelCase__      :			Optional[Any]=0.02, UpperCamelCase__      :			str=1e-12, UpperCamelCase__      :			Dict=0, UpperCamelCase__      :			Optional[Any]="topK", UpperCamelCase__      :			str="constant", UpperCamelCase__      :			Any=0.0, **UpperCamelCase__      :			Dict, )  ->			List[Any]:
        super().__init__(pad_token_id=UpperCamelCase__, **UpperCamelCase__     )

        _A    		=  vocab_size
        _A    		=  hidden_size
        _A    		=  num_hidden_layers
        _A    		=  num_attention_heads
        _A    		=  hidden_act
        _A    		=  intermediate_size
        _A    		=  hidden_dropout_prob
        _A    		=  attention_probs_dropout_prob
        _A    		=  max_position_embeddings
        _A    		=  type_vocab_size
        _A    		=  initializer_range
        _A    		=  layer_norm_eps
        _A    		=  pruning_method
        _A    		=  mask_init
        _A    		=  mask_scale





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


lowerCamelCase_    :			Optional[int]    =	{
    """configuration_graphormer""": ["""GRAPHORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GraphormerConfig"""],
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowerCamelCase_    :			Union[str, Any]    =	[
							    """GRAPHORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
							    """GraphormerForGraphClassification""",
							    """GraphormerModel""",
							    """GraphormerPreTrainedModel""",
							]


if TYPE_CHECKING:
							from .configuration_graphormer import GRAPHORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, GraphormerConfig

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_graphormer import (
														    GRAPHORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
														    GraphormerForGraphClassification,
														    GraphormerModel,
														    GraphormerPreTrainedModel,
														)


else:
							import sys

							lowerCamelCase_    :			Optional[Any]    =	_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)






